{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=gray size=4> week04 数据可视化案例 </font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 导入bokeh数据案例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using data directory: C:\\Users\\sxt\\.bokeh\\data\n",
      "Skipping 'CGM.csv' (checksum match)\n",
      "Skipping 'US_Counties.zip' (checksum match)\n",
      "Skipping 'us_cities.json' (checksum match)\n",
      "Skipping 'unemployment09.csv' (checksum match)\n",
      "Skipping 'AAPL.csv' (checksum match)\n",
      "Skipping 'FB.csv' (checksum match)\n",
      "Skipping 'GOOG.csv' (checksum match)\n",
      "Skipping 'IBM.csv' (checksum match)\n",
      "Skipping 'MSFT.csv' (checksum match)\n",
      "Skipping 'WPP2012_SA_DB03_POPULATION_QUINQUENNIAL.zip' (checksum match)\n",
      "Skipping 'gapminder_fertility.csv' (checksum match)\n",
      "Skipping 'gapminder_population.csv' (checksum match)\n",
      "Skipping 'gapminder_life_expectancy.csv' (checksum match)\n",
      "Skipping 'gapminder_regions.csv' (checksum match)\n",
      "Skipping 'world_cities.zip' (checksum match)\n",
      "Skipping 'airports.json' (checksum match)\n",
      "Skipping 'movies.db.zip' (checksum match)\n",
      "Skipping 'airports.csv' (checksum match)\n",
      "Skipping 'routes.csv' (checksum match)\n",
      "Skipping 'haarcascade_frontalface_default.xml' (checksum match)\n"
     ]
    }
   ],
   "source": [
    "import bokeh \n",
    "bokeh.sampledata.download()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"3144\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id != null && id in Bokeh.index) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var id = msg.content.text.trim();\n",
       "            if (id in Bokeh.index) {\n",
       "              Bokeh.index[id].model.document.clear();\n",
       "              delete Bokeh.index[id];\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[toinsert.length - 1]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"3144\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n",
       "\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      if (url in hashes) {\n",
       "        element.crossOrigin = \"anonymous\";\n",
       "        element.integrity = \"sha384-\" + hashes[url];\n",
       "      }\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  \n",
       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n",
       "  var css_urls = [];\n",
       "  \n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "    \n",
       "    \n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if (root.Bokeh !== undefined || force === true) {\n",
       "      \n",
       "    for (var i = 0; i < inline_js.length; i++) {\n",
       "      inline_js[i].call(root, root.Bokeh);\n",
       "    }\n",
       "    if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"3144\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"3144\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      if (url in hashes) {\n        element.crossOrigin = \"anonymous\";\n        element.integrity = \"sha384-\" + hashes[url];\n      }\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"3144\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bokeh.plotting import figure,output_notebook,show\n",
    "output_notebook() #在notebook文档中展示图像\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  上周案例回顾\n",
    " - 忘记参数可以用help的方法去查询"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"3777d9b3-bfd1-4571-856b-c4ff349511f9\" data-root-id=\"1002\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = {\"7d896bf2-c54c-4caa-ba8b-2c16eb41dc4e\":{\"roots\":{\"references\":[{\"attributes\":{\"below\":[{\"id\":\"1013\"}],\"center\":[{\"id\":\"1016\"},{\"id\":\"1020\"},{\"id\":\"1048\"}],\"left\":[{\"id\":\"1017\"}],\"plot_height\":400,\"plot_width\":400,\"renderers\":[{\"id\":\"1038\"}],\"title\":{\"id\":\"1003\"},\"toolbar\":{\"id\":\"1028\"},\"x_range\":{\"id\":\"1005\"},\"x_scale\":{\"id\":\"1009\"},\"y_range\":{\"id\":\"1007\"},\"y_scale\":{\"id\":\"1011\"}},\"id\":\"1002\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"1022\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"1021\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"1026\",\"type\":\"HelpTool\"},{\"attributes\":{\"overlay\":{\"id\":\"1027\"}},\"id\":\"1023\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"1024\",\"type\":\"SaveTool\"},{\"attributes\":{\"axis_label\":\"y\",\"formatter\":{\"id\":\"1043\"},\"ticker\":{\"id\":\"1018\"}},\"id\":\"1017\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1025\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"1018\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"1043\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"source\":{\"id\":\"1035\"}},\"id\":\"1039\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"1007\",\"type\":\"DataRange1d\"},{\"attributes\":{\"axis\":{\"id\":\"1017\"},\"dimension\":1,\"ticker\":null},\"id\":\"1020\",\"type\":\"Grid\"},{\"attributes\":{\"items\":[{\"id\":\"1049\"}]},\"id\":\"1048\",\"type\":\"Legend\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1037\",\"type\":\"Line\"},{\"attributes\":{\"data\":{\"x\":[1,3,5,7,9],\"y\":[2,4,6,8,4]},\"selected\":{\"id\":\"1047\"},\"selection_policy\":{\"id\":\"1046\"}},\"id\":\"1035\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"1005\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"1011\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1041\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"1014\",\"type\":\"BasicTicker\"},{\"attributes\":{\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1036\",\"type\":\"Line\"},{\"attributes\":{\"label\":{\"value\":\"temp\"},\"renderers\":[{\"id\":\"1038\"}]},\"id\":\"1049\",\"type\":\"LegendItem\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1021\"},{\"id\":\"1022\"},{\"id\":\"1023\"},{\"id\":\"1024\"},{\"id\":\"1025\"},{\"id\":\"1026\"}]},\"id\":\"1028\",\"type\":\"Toolbar\"},{\"attributes\":{\"axis_label\":\"x\",\"formatter\":{\"id\":\"1041\"},\"ticker\":{\"id\":\"1014\"}},\"id\":\"1013\",\"type\":\"LinearAxis\"},{\"attributes\":{\"axis\":{\"id\":\"1013\"},\"ticker\":null},\"id\":\"1016\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1009\",\"type\":\"LinearScale\"},{\"attributes\":{\"text\":\"line example\"},\"id\":\"1003\",\"type\":\"Title\"},{\"attributes\":{\"data_source\":{\"id\":\"1035\"},\"glyph\":{\"id\":\"1036\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1037\"},\"selection_glyph\":null,\"view\":{\"id\":\"1039\"}},\"id\":\"1038\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":0.5,\"fill_color\":\"lightgrey\",\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[4,4],\"line_width\":2,\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1027\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"1046\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1047\",\"type\":\"Selection\"}],\"root_ids\":[\"1002\"]},\"title\":\"Bokeh Application\",\"version\":\"2.1.1\"}};\n",
       "  var render_items = [{\"docid\":\"7d896bf2-c54c-4caa-ba8b-2c16eb41dc4e\",\"root_ids\":[\"1002\"],\"roots\":{\"1002\":\"3777d9b3-bfd1-4571-856b-c4ff349511f9\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1002"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 01\n",
    "x = [1,3,5,7,9]\n",
    "y = [2,4,6,8,4]\n",
    "p = figure(title=\"line example\",\n",
    "          x_axis_label='x',\n",
    "          y_axis_label='y',\n",
    "          width=400,\n",
    "          height=400)\n",
    "\n",
    "\n",
    "\n",
    "p.line(x,y,legend_label=\"temp\",line_width=2)\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"ce8f5aed-cb75-4d65-bf9d-d64f09346274\" data-root-id=\"1106\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = {\"3f6d59ca-3f76-41f6-b8c7-5efb13202a2b\":{\"roots\":{\"references\":[{\"attributes\":{\"below\":[{\"id\":\"1117\"}],\"center\":[{\"id\":\"1120\"},{\"id\":\"1124\"}],\"left\":[{\"id\":\"1121\"}],\"plot_height\":400,\"plot_width\":400,\"renderers\":[{\"id\":\"1142\"}],\"title\":{\"id\":\"1107\"},\"toolbar\":{\"id\":\"1132\"},\"x_range\":{\"id\":\"1109\"},\"x_scale\":{\"id\":\"1113\"},\"y_range\":{\"id\":\"1111\"},\"y_scale\":{\"id\":\"1115\"}},\"id\":\"1106\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"1115\",\"type\":\"LinearScale\"},{\"attributes\":{\"axis\":{\"id\":\"1121\"},\"dimension\":1,\"ticker\":null},\"id\":\"1124\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1126\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"1159\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"1113\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1158\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1125\",\"type\":\"PanTool\"},{\"attributes\":{\"text\":\"multi_line\"},\"id\":\"1107\",\"type\":\"Title\"},{\"attributes\":{\"overlay\":{\"id\":\"1131\"}},\"id\":\"1127\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"1130\",\"type\":\"HelpTool\"},{\"attributes\":{\"axis\":{\"id\":\"1117\"},\"ticker\":null},\"id\":\"1120\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1155\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"1129\",\"type\":\"ResetTool\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"field\":\"line_color\"},\"line_width\":{\"field\":\"line_width\"},\"xs\":{\"field\":\"xs\"},\"ys\":{\"field\":\"ys\"}},\"id\":\"1141\",\"type\":\"MultiLine\"},{\"attributes\":{\"formatter\":{\"id\":\"1155\"},\"ticker\":{\"id\":\"1122\"}},\"id\":\"1121\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1122\",\"type\":\"BasicTicker\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1125\"},{\"id\":\"1126\"},{\"id\":\"1127\"},{\"id\":\"1128\"},{\"id\":\"1129\"},{\"id\":\"1130\"}]},\"id\":\"1132\",\"type\":\"Toolbar\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":0.5,\"fill_color\":\"lightgrey\",\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[4,4],\"line_width\":2,\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1131\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"data\":{\"line_alpha\":[0.4,0.8],\"line_color\":[\"navy\",\"firebrick\"],\"line_width\":[3,4],\"xs\":[[2,4,6,8],[1,3,5,7,9]],\"ys\":[[3,4,2,1],[4,5,2,8,6]]},\"selected\":{\"id\":\"1159\"},\"selection_policy\":{\"id\":\"1158\"}},\"id\":\"1139\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"source\":{\"id\":\"1139\"}},\"id\":\"1143\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"1128\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"1118\",\"type\":\"BasicTicker\"},{\"attributes\":{\"line_alpha\":{\"field\":\"line_alpha\"},\"line_color\":{\"field\":\"line_color\"},\"line_width\":{\"field\":\"line_width\"},\"xs\":{\"field\":\"xs\"},\"ys\":{\"field\":\"ys\"}},\"id\":\"1140\",\"type\":\"MultiLine\"},{\"attributes\":{},\"id\":\"1153\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"formatter\":{\"id\":\"1153\"},\"ticker\":{\"id\":\"1118\"}},\"id\":\"1117\",\"type\":\"LinearAxis\"},{\"attributes\":{\"data_source\":{\"id\":\"1139\"},\"glyph\":{\"id\":\"1140\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1141\"},\"selection_glyph\":null,\"view\":{\"id\":\"1143\"}},\"id\":\"1142\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"1109\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"1111\",\"type\":\"DataRange1d\"}],\"root_ids\":[\"1106\"]},\"title\":\"Bokeh Application\",\"version\":\"2.1.1\"}};\n",
       "  var render_items = [{\"docid\":\"3f6d59ca-3f76-41f6-b8c7-5efb13202a2b\",\"root_ids\":[\"1106\"],\"roots\":{\"1106\":\"ce8f5aed-cb75-4d65-bf9d-d64f09346274\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1106"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=[[2,4,6,8],[1,3,5,7,9]]\n",
    "y=[[3,4,2,1],[4,5,2,8,6]]\n",
    "\n",
    "#画布\n",
    "p=figure(plot_width=400,\n",
    "        plot_height=400,\n",
    "        title=\"multi_line\")\n",
    "\n",
    "p.multi_line(x,y,color=['navy','firebrick'],alpha=[0.4,0.8],line_width=[3,4])\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 折线图实践"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 示例代码（数学模型）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "BokehDeprecationWarning: 'legend' keyword is deprecated, use explicit 'legend_label', 'legend_field', or 'legend_group' keywords instead\n",
      "BokehDeprecationWarning: 'legend' keyword is deprecated, use explicit 'legend_label', 'legend_field', or 'legend_group' keywords instead\n",
      "BokehDeprecationWarning: 'legend' keyword is deprecated, use explicit 'legend_label', 'legend_field', or 'legend_group' keywords instead\n",
      "BokehDeprecationWarning: 'legend' keyword is deprecated, use explicit 'legend_label', 'legend_field', or 'legend_group' keywords instead\n",
      "BokehDeprecationWarning: 'legend' keyword is deprecated, use explicit 'legend_label', 'legend_field', or 'legend_group' keywords instead\n",
      "BokehDeprecationWarning: 'legend' keyword is deprecated, use explicit 'legend_label', 'legend_field', or 'legend_group' keywords instead\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"a4bde049-590d-4a85-a68e-d7676b4f3880\" data-root-id=\"1208\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = 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"screen\",\"value\":5},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1253\",\"type\":\"Circle\"},{\"attributes\":{\"label\":{\"value\":\"y=10^x\"},\"renderers\":[{\"id\":\"1288\"},{\"id\":\"1308\"}]},\"id\":\"1304\",\"type\":\"LegendItem\"},{\"attributes\":{},\"id\":\"1248\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1217\",\"type\":\"LogScale\"},{\"attributes\":{\"line_color\":\"green\",\"line_width\":3,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1268\",\"type\":\"Line\"},{\"attributes\":{\"label\":{\"value\":\"y=x^2\"},\"renderers\":[{\"id\":\"1270\"}]},\"id\":\"1284\",\"type\":\"LegendItem\"},{\"attributes\":{\"source\":{\"id\":\"1267\"}},\"id\":\"1271\",\"type\":\"CDSView\"},{\"attributes\":{\"num_minor_ticks\":10},\"id\":\"1224\",\"type\":\"LogTicker\"},{\"attributes\":{},\"id\":\"1324\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1325\",\"type\":\"Selection\"}],\"root_ids\":[\"1208\"]},\"title\":\"Bokeh Application\",\"version\":\"2.1.1\"}};\n",
       "  var render_items = [{\"docid\":\"ceea96b7-2010-42f0-afe9-443c72c237af\",\"root_ids\":[\"1208\"],\"roots\":{\"1208\":\"a4bde049-590d-4a85-a68e-d7676b4f3880\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1208"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# # 数据准备\n",
    "x = [0.1,0.5,1.0,1.5,2.0,2.5,3.0]\n",
    "y0=[i**2 for i in x]\n",
    "y1=[10**i for i in x]\n",
    "y2=[10**(i**2) for i in x]\n",
    "\n",
    "\n",
    "\n",
    "# #tools工具说明可以自定义https://docs.bokeh.org/en/latest/docs/user_guide/tools.html，不写就默认\n",
    "p=figure(\n",
    "    tools=\"pan,box_zoom,reset,save\",\n",
    "    y_axis_type=\"log\",title=\"log axis eample\",\n",
    "    x_axis_label=\"section\",y_axis_label=\"paticles\",\n",
    "    width=500,height=500\n",
    ")\n",
    "\n",
    "\n",
    "p.line(x,x,legend=\"y=x\",line_width=2)\n",
    "p.circle(x,x,legend=\"y=x\",fill_color=\"white\",size=5,line_width=3)\n",
    "p.line(x,y0,legend=\"y=x^2\",line_color=\"green\",line_width=3)\n",
    "p.line(x,y1,legend=\"y=10^x\",line_color=\"red\",line_width=3)\n",
    "p.circle(x,y1,legend=\"y=10^x\",fill_color=\"white\",color=\"red\",size=6)\n",
    "p.line(x,y2,legend=\"y=10^x^n\",color=\"black\",line_dash=\"4 4\")\n",
    "\n",
    "\n",
    "\n",
    "# # 图例设置:位置 ，点击隐藏\n",
    "p.legend.location=\"top_left\"\n",
    "p.legend.click_policy=\"hide\"\n",
    "#p.legend.click_policy=\"mute\"\n",
    "\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 案例实操"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 离婚率数据，折线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Marriages</th>\n",
       "      <th>Divorces</th>\n",
       "      <th>Population</th>\n",
       "      <th>Marriages_per_1000</th>\n",
       "      <th>Divorces_per_1000</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1867</td>\n",
       "      <td>357000.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>36970000</td>\n",
       "      <td>9.7</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1868</td>\n",
       "      <td>345000.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>37885000</td>\n",
       "      <td>9.1</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1869</td>\n",
       "      <td>348000.0</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>38870000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1870</td>\n",
       "      <td>352000.0</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>39905000</td>\n",
       "      <td>8.8</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1871</td>\n",
       "      <td>359000.0</td>\n",
       "      <td>12000.0</td>\n",
       "      <td>41010000</td>\n",
       "      <td>8.8</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>2007</td>\n",
       "      <td>2197000.0</td>\n",
       "      <td>856000.0</td>\n",
       "      <td>301696000</td>\n",
       "      <td>7.3</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2008</td>\n",
       "      <td>2157000.0</td>\n",
       "      <td>844000.0</td>\n",
       "      <td>304543000</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>2009</td>\n",
       "      <td>2080000.0</td>\n",
       "      <td>840000.0</td>\n",
       "      <td>307240000</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2010</td>\n",
       "      <td>2096000.0</td>\n",
       "      <td>872000.0</td>\n",
       "      <td>309776000</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>2011</td>\n",
       "      <td>2118000.0</td>\n",
       "      <td>877000.0</td>\n",
       "      <td>312034000</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>145 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Year  Marriages  Divorces  Population  Marriages_per_1000  \\\n",
       "0    1867   357000.0   10000.0    36970000                 9.7   \n",
       "1    1868   345000.0   10000.0    37885000                 9.1   \n",
       "2    1869   348000.0   11000.0    38870000                 9.0   \n",
       "3    1870   352000.0   11000.0    39905000                 8.8   \n",
       "4    1871   359000.0   12000.0    41010000                 8.8   \n",
       "..    ...        ...       ...         ...                 ...   \n",
       "140  2007  2197000.0  856000.0   301696000                 7.3   \n",
       "141  2008  2157000.0  844000.0   304543000                 7.1   \n",
       "142  2009  2080000.0  840000.0   307240000                 6.8   \n",
       "143  2010  2096000.0  872000.0   309776000                 6.8   \n",
       "144  2011  2118000.0  877000.0   312034000                 6.8   \n",
       "\n",
       "     Divorces_per_1000  \n",
       "0                  0.3  \n",
       "1                  0.3  \n",
       "2                  0.3  \n",
       "3                  0.3  \n",
       "4                  0.3  \n",
       "..                 ...  \n",
       "140                2.8  \n",
       "141                2.8  \n",
       "142                2.7  \n",
       "143                2.8  \n",
       "144                2.8  \n",
       "\n",
       "[145 rows x 6 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  获取数据\n",
    "\n",
    "\n",
    "\n",
    "from bokeh.models import ColumnDataSource, NumeralTickFormatter, SingleIntervalTicker\n",
    "from bokeh.sampledata.us_marriages_divorces import data\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Marriages</th>\n",
       "      <th>Divorces</th>\n",
       "      <th>Population</th>\n",
       "      <th>Marriages_per_1000</th>\n",
       "      <th>Divorces_per_1000</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1867</td>\n",
       "      <td>357000.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>36970000</td>\n",
       "      <td>9.7</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1868</td>\n",
       "      <td>345000.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>37885000</td>\n",
       "      <td>9.1</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1869</td>\n",
       "      <td>348000.0</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>38870000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1870</td>\n",
       "      <td>352000.0</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>39905000</td>\n",
       "      <td>8.8</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1871</td>\n",
       "      <td>359000.0</td>\n",
       "      <td>12000.0</td>\n",
       "      <td>41010000</td>\n",
       "      <td>8.8</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>2007</td>\n",
       "      <td>2197000.0</td>\n",
       "      <td>856000.0</td>\n",
       "      <td>301696000</td>\n",
       "      <td>7.3</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2008</td>\n",
       "      <td>2157000.0</td>\n",
       "      <td>844000.0</td>\n",
       "      <td>304543000</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>2009</td>\n",
       "      <td>2080000.0</td>\n",
       "      <td>840000.0</td>\n",
       "      <td>307240000</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2010</td>\n",
       "      <td>2096000.0</td>\n",
       "      <td>872000.0</td>\n",
       "      <td>309776000</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>2011</td>\n",
       "      <td>2118000.0</td>\n",
       "      <td>877000.0</td>\n",
       "      <td>312034000</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>145 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Year  Marriages  Divorces  Population  Marriages_per_1000  \\\n",
       "0    1867   357000.0   10000.0    36970000                 9.7   \n",
       "1    1868   345000.0   10000.0    37885000                 9.1   \n",
       "2    1869   348000.0   11000.0    38870000                 9.0   \n",
       "3    1870   352000.0   11000.0    39905000                 8.8   \n",
       "4    1871   359000.0   12000.0    41010000                 8.8   \n",
       "..    ...        ...       ...         ...                 ...   \n",
       "140  2007  2197000.0  856000.0   301696000                 7.3   \n",
       "141  2008  2157000.0  844000.0   304543000                 7.1   \n",
       "142  2009  2080000.0  840000.0   307240000                 6.8   \n",
       "143  2010  2096000.0  872000.0   309776000                 6.8   \n",
       "144  2011  2118000.0  877000.0   312034000                 6.8   \n",
       "\n",
       "     Divorces_per_1000  \n",
       "0                  0.3  \n",
       "1                  0.3  \n",
       "2                  0.3  \n",
       "3                  0.3  \n",
       "4                  0.3  \n",
       "..                 ...  \n",
       "140                2.8  \n",
       "141                2.8  \n",
       "142                2.7  \n",
       "143                2.8  \n",
       "144                2.8  \n",
       "\n",
       "[145 rows x 6 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  选取数据\n",
    "\n",
    "\n",
    "#  填充空缺值\n",
    "data = data.interpolate(method=\"linear\",axis=0).ffill().bfill()\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 上述的数据表格是一个字典dict的形式，查看数据要符合字典的取值形式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      1867\n",
       "1      1868\n",
       "2      1869\n",
       "3      1870\n",
       "4      1871\n",
       "       ... \n",
       "140    2007\n",
       "141    2008\n",
       "142    2009\n",
       "143    2010\n",
       "144    2011\n",
       "Name: Year, Length: 145, dtype: int64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 看看具体的数据,以字典的形式取值\n",
    "data.Year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1867, 1868, 1869, 1870, 1871, 1872, 1873, 1874, 1875, 1876, 1877,\n",
       "       1878, 1879, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888,\n",
       "       1889, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899,\n",
       "       1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910,\n",
       "       1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921,\n",
       "       1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932,\n",
       "       1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943,\n",
       "       1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954,\n",
       "       1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965,\n",
       "       1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976,\n",
       "       1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987,\n",
       "       1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998,\n",
       "       1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009,\n",
       "       2010, 2011], dtype=int64)"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.Year.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 9.7       ,  9.1       ,  9.        ,  8.8       ,  8.8       ,\n",
       "        9.        ,  8.9       ,  8.7       ,  9.        ,  8.7       ,\n",
       "        8.7       ,  8.8       ,  8.9       ,  9.        ,  9.        ,\n",
       "        9.2       ,  9.2       ,  8.7       ,  8.9       ,  9.2       ,\n",
       "        8.6       ,  8.8       ,  9.1       ,  9.        ,  9.2       ,\n",
       "        9.1       ,  8.9       ,  8.5       ,  8.8       ,  8.9       ,\n",
       "        8.9       ,  8.8       ,  9.        ,  9.3       ,  9.6       ,\n",
       "        9.8       , 10.1       ,  9.9       , 10.        , 10.5       ,\n",
       "       10.8       ,  9.7       ,  9.9       , 10.3       , 10.2       ,\n",
       "       10.5       , 10.5       , 10.3       , 10.        , 10.6       ,\n",
       "       11.1       ,  9.6       , 10.9       , 12.        , 10.7       ,\n",
       "       10.3       , 11.        , 10.4       , 10.3       , 10.2       ,\n",
       "       10.1       ,  9.8       , 10.1       ,  9.1       ,  8.5       ,\n",
       "        7.9       ,  8.7       , 10.3       , 10.4       , 10.7       ,\n",
       "       11.3       , 10.2       , 10.7       , 12.1       , 12.7       ,\n",
       "       13.1       , 11.5       , 10.5       , 11.5       , 16.2       ,\n",
       "       13.8       , 12.4       , 10.6       , 11.        , 10.3       ,\n",
       "        9.8       ,  9.7       ,  9.2       ,  9.3       ,  9.4       ,\n",
       "        8.9       ,  8.3       ,  8.4       ,  8.4       ,  8.4       ,\n",
       "        8.5       ,  8.7       ,  9.        ,  9.3       ,  9.4       ,\n",
       "        9.7       , 10.3       , 10.6       , 10.7       , 10.5       ,\n",
       "       10.9       , 10.8       , 10.5       , 10.        ,  9.9       ,\n",
       "        9.9       , 10.3       , 10.4       , 10.6       , 10.6       ,\n",
       "       10.56666667, 10.53333333, 10.5       , 10.1       , 10.        ,\n",
       "        9.9       ,  9.7       ,  9.7       ,  9.8       ,  9.4       ,\n",
       "        9.3       ,  9.        ,  9.1       ,  8.96666667,  8.83333333,\n",
       "        8.7       ,  8.1       ,  8.4       ,  8.2       ,  8.2       ,\n",
       "        8.        ,  7.7       ,  7.8       ,  7.6       ,  7.3       ,\n",
       "        7.3       ,  7.1       ,  6.8       ,  6.8       ,  6.8       ])"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.Marriages_per_1000.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"display: table;\"><div style=\"display: table-row;\"><div style=\"display: table-cell;\"><b title=\"bokeh.models.sources.ColumnDataSource\">ColumnDataSource</b>(</div><div style=\"display: table-cell;\">id&nbsp;=&nbsp;'3681', <span id=\"3683\" style=\"cursor: pointer;\">&hellip;)</span></div></div><div class=\"3682\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">data&nbsp;=&nbsp;{'marriages': {'__ndarray__': 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'shape': (145,), 'dtype': 'float64', 'order': 'little'}, 'year': [1867, 1868, 1869, 1870, 1871, 1872, 1873, 1874, 1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011], 'divorces': {'__ndarray__': 'AAAAAACIw0AAAAAAAIjDQAAAAAAAfMVAAAAAAAB8xUAAAAAAAHDHQAAAAAAAcMdAAAAAAABkyUAAAAAAAFjLQAAAAAAAWMtAAAAAAABMzUAAAAAAAEDPQAAAAAAAQM9AAAAAAACa0EAAAAAAAIjTQAAAAAAAgtRAAAAAAAB81UAAAAAAAHbWQAAAAAAAdtZAAAAAAAB21kAAAAAAAGTZQAAAAAAAWNtAAAAAAABS3EAAAAAAAEDfQAAAAAAAHeBAAAAAAACU4UAAAAAAABHiQAAAAAAAEeJAAAAAAACO4kAAAAAAAIjjQAAAAAAA/+RAAAAAAAD55UAAAAAAAHDnQAAAAAAA5+hAAAAAAABY60AAAAAAAMntQAAAAAAAye1AAAAAAAC970AAAAAAAB3wQAAAAAAAmvBAAAAAAACU8UAAAAAAgMzyQAAAAACAzPJAAAAAAACI80AAAAAAgEP0QAAAAACAuvVAAAAAAADz9kAAAAAAgDf2QAAAAACAqPhAAAAAAABk+UAAAAAAANX7QAAAAAAAyf1AAAAAAABS/EAAAAAAgFUBQQAAAADA3wRBAAAAAACIA0EAAAAAQDACQQAAAABAJARBAAAAAMDfBEEAAAAAwFwFQQAAAABAlQZBAAAAAADtB0EAAAAAAGoIQQAAAACAJQlBAAAAAADtB0EAAAAAAPMGQQAAAAAABQRBAAAAAEAkBEEAAAAAAOcIQQAAAACAnApBAAAAAADPDEEAAAAAQGUOQQAAAAAAyQ1BAAAAAMCjDkEAAAAAAB0QQQAAAAAg4hFBAAAAAKCXE0EAAAAAYOkVQQAAAAAAahhBAAAAACCaHUEAAAAAoJ0iQQAAAADgeh1BAAAAAADnGEEAAAAAIDsYQQAAAACgfxdBAAAAACBBF0EAAAAAAO0XQQAAAADAzRdBAAAAAOAhF0EAAAAAoAIXQQAAAADAUBdBAAAAACBBF0EAAAAAAHYWQQAAAADgGxhBAAAAAKD8F0EAAAAAwEQZQQAAAAAgNRlBAAAAAIAfGkEAAAAAQHcbQQAAAABgPB1BAAAAAOB0HkEAAAAA4OsfQQAAAACA0iFBAAAAADCAI0EAAAAAQJslQQAAAAAQlydBAAAAAJDJKUEAAAAAcOwrQQAAAAD2Bi5BAAAAAEqjL0EAAAAAfqMwQQAAAACFzjBBAAAAADBTMUEAAAAAZjQyQQAAAACvETJBAAAAAOKZMkGrqqqqnGkyQVVVVVVXOTJBAAAAABIJMkEAAAAAUjIyQQAAAADT/jFBAAAAAE7JMUEAAAAAK5MxQQAAAADfvTFBAAAAACvxMUEAAAAApy4yQQAAAABK0TJBAAAAAPFEMkEAAAAA9X0yQVVVVVVLPjJBq6qqqqH+MUEAAAAA+L4xQQAAAACYUTFBAAAAAJ15MUEAAAAAAM8sQQAAAADAryxBAAAAAPAkLUEAAAAAMEosQQAAAAAw0ypBAAAAADDZKUEAAAAAgJwqQQAAAACAHypBAAAAAMDBKUEAAAAAgKIpQQAAAACAnCpBAAAAAJDDKkE=', 'shape': (145,), 'dtype': 'float64', 'order': 'little'}},</div></div><div class=\"3682\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">js_event_callbacks&nbsp;=&nbsp;{},</div></div><div class=\"3682\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">js_property_callbacks&nbsp;=&nbsp;{},</div></div><div class=\"3682\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">name&nbsp;=&nbsp;None,</div></div><div class=\"3682\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">selected&nbsp;=&nbsp;Selection(id='3685', ...),</div></div><div class=\"3682\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">selection_policy&nbsp;=&nbsp;UnionRenderers(id='3684', ...),</div></div><div class=\"3682\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">subscribed_events&nbsp;=&nbsp;[],</div></div><div class=\"3682\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">tags&nbsp;=&nbsp;[])</div></div></div>\n",
       "<script>\n",
       "(function() {\n",
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       "    for (var i = 0; i < rows.length; i++) {\n",
       "      var el = rows[i];\n",
       "      el.style.display = expanded ? \"none\" : \"table-row\";\n",
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       "    ellipsis.innerHTML = expanded ? \"&hellip;)\" : \"&lsaquo;&lsaquo;&lsaquo;\";\n",
       "    expanded = !expanded;\n",
       "  });\n",
       "})();\n",
       "</script>\n"
      ],
      "text/plain": [
       "ColumnDataSource(id='3681', ...)"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 把数据变成字典\n",
    "\n",
    "source = ColumnDataSource (data=dict(year = data.Year.values,\n",
    "     marriages = data.Marriages.values,\n",
    "     divorces = data.Divorces.values\n",
    "    ))\n",
    "\n",
    "source"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Marriages</th>\n",
       "      <th>Divorces</th>\n",
       "      <th>Population</th>\n",
       "      <th>Marriages_per_1000</th>\n",
       "      <th>Divorces_per_1000</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1867</td>\n",
       "      <td>357000.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>36970000</td>\n",
       "      <td>9.7</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1868</td>\n",
       "      <td>345000.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>37885000</td>\n",
       "      <td>9.1</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1869</td>\n",
       "      <td>348000.0</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>38870000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1870</td>\n",
       "      <td>352000.0</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>39905000</td>\n",
       "      <td>8.8</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1871</td>\n",
       "      <td>359000.0</td>\n",
       "      <td>12000.0</td>\n",
       "      <td>41010000</td>\n",
       "      <td>8.8</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>2007</td>\n",
       "      <td>2197000.0</td>\n",
       "      <td>856000.0</td>\n",
       "      <td>301696000</td>\n",
       "      <td>7.3</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2008</td>\n",
       "      <td>2157000.0</td>\n",
       "      <td>844000.0</td>\n",
       "      <td>304543000</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>2009</td>\n",
       "      <td>2080000.0</td>\n",
       "      <td>840000.0</td>\n",
       "      <td>307240000</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2010</td>\n",
       "      <td>2096000.0</td>\n",
       "      <td>872000.0</td>\n",
       "      <td>309776000</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>2011</td>\n",
       "      <td>2118000.0</td>\n",
       "      <td>877000.0</td>\n",
       "      <td>312034000</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>145 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Year  Marriages  Divorces  Population  Marriages_per_1000  \\\n",
       "0    1867   357000.0   10000.0    36970000                 9.7   \n",
       "1    1868   345000.0   10000.0    37885000                 9.1   \n",
       "2    1869   348000.0   11000.0    38870000                 9.0   \n",
       "3    1870   352000.0   11000.0    39905000                 8.8   \n",
       "4    1871   359000.0   12000.0    41010000                 8.8   \n",
       "..    ...        ...       ...         ...                 ...   \n",
       "140  2007  2197000.0  856000.0   301696000                 7.3   \n",
       "141  2008  2157000.0  844000.0   304543000                 7.1   \n",
       "142  2009  2080000.0  840000.0   307240000                 6.8   \n",
       "143  2010  2096000.0  872000.0   309776000                 6.8   \n",
       "144  2011  2118000.0  877000.0   312034000                 6.8   \n",
       "\n",
       "     Divorces_per_1000  \n",
       "0                  0.3  \n",
       "1                  0.3  \n",
       "2                  0.3  \n",
       "3                  0.3  \n",
       "4                  0.3  \n",
       "..                 ...  \n",
       "140                2.8  \n",
       "141                2.8  \n",
       "142                2.7  \n",
       "143                2.8  \n",
       "144                2.8  \n",
       "\n",
       "[145 rows x 6 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
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   "source": [
    "# 设置工具条\n",
    "\n",
    "\n",
    "# 工具条\n",
    "TOOLS = 'pan,wheel_zoom,box_zoom,reset,save'\n",
    "# 画布\n",
    "p = figure(tools=TOOLS, plot_width=800, plot_height=500,\n",
    "           tooltips='<font face=\"Arial\" size=\"3\">@$name{0.0} $name per 1,000 people in @year</font>') #增加交互的代码\n",
    "# 其他自定义属性\n",
    "p.hover.mode = 'vline'\n",
    "p.xaxis.ticker = SingleIntervalTicker(interval=10, num_minor_ticks=0)\n",
    "p.yaxis.formatter = NumeralTickFormatter(format='0.0a')\n",
    "p.yaxis.axis_label = '# per 1,000 people'\n",
    "p.title.text = '144 years of marriage and divorce in the U.S.'\n",
    "# 绘图\n",
    "p.line('year', 'marriages', color='#1f77b4', line_width=3, source=source, name=\"marriages\")\n",
    "p.line('year', 'divorces', color='#ff7f0e', line_width=3, source=source, name=\"divorces\")\n",
    "# 显示\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 股市数据折线图案例：时间数值型数据的转换"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "## 准备工作，导入数据\n",
    "\n",
    "import numpy as np\n",
    "from bokeh.models import ColumnDataSource, CustomJSTransform,SingleIntervalTicker\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.io import output_file, show\n",
    "from bokeh.sampledata.stocks import AAPL, GOOG\n",
    "from bokeh.transform import transform\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 查看数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'date': ['2000-03-01',\n",
       "  '2000-03-02',\n",
       "  '2000-03-03',\n",
       "  '2000-03-06',\n",
       "  '2000-03-07',\n",
       "  '2000-03-08',\n",
       "  '2000-03-09',\n",
       "  '2000-03-10',\n",
       "  '2000-03-13',\n",
       "  '2000-03-14',\n",
       "  '2000-03-15',\n",
       "  '2000-03-16',\n",
       "  '2000-03-17',\n",
       "  '2000-03-20',\n",
       "  '2000-03-21',\n",
       "  '2000-03-22',\n",
       "  '2000-03-23',\n",
       "  '2000-03-24',\n",
       "  '2000-03-27',\n",
       "  '2000-03-28',\n",
       "  '2000-03-29',\n",
       "  '2000-03-30',\n",
       "  '2000-03-31',\n",
       "  '2000-04-03',\n",
       "  '2000-04-04',\n",
       "  '2000-04-05',\n",
       "  '2000-04-06',\n",
       "  '2000-04-07',\n",
       "  '2000-04-10',\n",
       "  '2000-04-11',\n",
       "  '2000-04-12',\n",
       "  '2000-04-13',\n",
       "  '2000-04-14',\n",
       "  '2000-04-17',\n",
       "  '2000-04-18',\n",
       "  '2000-04-19',\n",
       "  '2000-04-20',\n",
       "  '2000-04-24',\n",
       "  '2000-04-25',\n",
       "  '2000-04-26',\n",
       "  '2000-04-27',\n",
       "  '2000-04-28',\n",
       "  '2000-05-01',\n",
       "  '2000-05-02',\n",
       "  '2000-05-03',\n",
       "  '2000-05-04',\n",
       "  '2000-05-05',\n",
       "  '2000-05-08',\n",
       "  '2000-05-09',\n",
       "  '2000-05-10',\n",
       "  '2000-05-11',\n",
       "  '2000-05-12',\n",
       "  '2000-05-15',\n",
       "  '2000-05-16',\n",
       "  '2000-05-17',\n",
       "  '2000-05-18',\n",
       "  '2000-05-19',\n",
       "  '2000-05-22',\n",
       "  '2000-05-23',\n",
       "  '2000-05-24',\n",
       "  '2000-05-25',\n",
       "  '2000-05-26',\n",
       "  '2000-05-30',\n",
       "  '2000-05-31',\n",
       "  '2000-06-01',\n",
       "  '2000-06-02',\n",
       "  '2000-06-05',\n",
       "  '2000-06-06',\n",
       "  '2000-06-07',\n",
       "  '2000-06-08',\n",
       "  '2000-06-09',\n",
       "  '2000-06-12',\n",
       "  '2000-06-13',\n",
       "  '2000-06-14',\n",
       "  '2000-06-15',\n",
       "  '2000-06-16',\n",
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       "  '2002-10-16',\n",
       "  '2002-10-17',\n",
       "  '2002-10-18',\n",
       "  '2002-10-21',\n",
       "  '2002-10-22',\n",
       "  '2002-10-23',\n",
       "  '2002-10-24',\n",
       "  '2002-10-25',\n",
       "  '2002-10-28',\n",
       "  '2002-10-29',\n",
       "  '2002-10-30',\n",
       "  '2002-10-31',\n",
       "  '2002-11-01',\n",
       "  '2002-11-04',\n",
       "  '2002-11-05',\n",
       "  '2002-11-06',\n",
       "  '2002-11-07',\n",
       "  '2002-11-08',\n",
       "  '2002-11-11',\n",
       "  '2002-11-12',\n",
       "  '2002-11-13',\n",
       "  '2002-11-14',\n",
       "  '2002-11-15',\n",
       "  '2002-11-18',\n",
       "  '2002-11-19',\n",
       "  '2002-11-20',\n",
       "  '2002-11-21',\n",
       "  '2002-11-22',\n",
       "  '2002-11-25',\n",
       "  '2002-11-26',\n",
       "  '2002-11-27',\n",
       "  '2002-11-29',\n",
       "  '2002-12-02',\n",
       "  '2002-12-03',\n",
       "  '2002-12-04',\n",
       "  '2002-12-05',\n",
       "  '2002-12-06',\n",
       "  '2002-12-09',\n",
       "  '2002-12-10',\n",
       "  '2002-12-11',\n",
       "  '2002-12-12',\n",
       "  '2002-12-13',\n",
       "  '2002-12-16',\n",
       "  '2002-12-17',\n",
       "  '2002-12-18',\n",
       "  '2002-12-19',\n",
       "  '2002-12-20',\n",
       "  '2002-12-23',\n",
       "  '2002-12-24',\n",
       "  '2002-12-26',\n",
       "  '2002-12-27',\n",
       "  '2002-12-30',\n",
       "  '2002-12-31',\n",
       "  '2003-01-02',\n",
       "  '2003-01-03',\n",
       "  '2003-01-06',\n",
       "  '2003-01-07',\n",
       "  '2003-01-08',\n",
       "  '2003-01-09',\n",
       "  '2003-01-10',\n",
       "  '2003-01-13',\n",
       "  '2003-01-14',\n",
       "  '2003-01-15',\n",
       "  '2003-01-16',\n",
       "  '2003-01-17',\n",
       "  '2003-01-21',\n",
       "  '2003-01-22',\n",
       "  '2003-01-23',\n",
       "  '2003-01-24',\n",
       "  '2003-01-27',\n",
       "  '2003-01-28',\n",
       "  '2003-01-29',\n",
       "  '2003-01-30',\n",
       "  '2003-01-31',\n",
       "  '2003-02-03',\n",
       "  '2003-02-04',\n",
       "  '2003-02-05',\n",
       "  '2003-02-06',\n",
       "  '2003-02-07',\n",
       "  '2003-02-10',\n",
       "  '2003-02-11',\n",
       "  '2003-02-12',\n",
       "  '2003-02-13',\n",
       "  '2003-02-14',\n",
       "  '2003-02-18',\n",
       "  '2003-02-19',\n",
       "  '2003-02-20',\n",
       "  '2003-02-21',\n",
       "  '2003-02-24',\n",
       "  '2003-02-25',\n",
       "  '2003-02-26',\n",
       "  '2003-02-27',\n",
       "  '2003-02-28',\n",
       "  '2003-03-03',\n",
       "  '2003-03-04',\n",
       "  '2003-03-05',\n",
       "  '2003-03-06',\n",
       "  '2003-03-07',\n",
       "  '2003-03-10',\n",
       "  '2003-03-11',\n",
       "  '2003-03-12',\n",
       "  '2003-03-13',\n",
       "  '2003-03-14',\n",
       "  '2003-03-17',\n",
       "  '2003-03-18',\n",
       "  '2003-03-19',\n",
       "  '2003-03-20',\n",
       "  '2003-03-21',\n",
       "  '2003-03-24',\n",
       "  '2003-03-25',\n",
       "  '2003-03-26',\n",
       "  '2003-03-27',\n",
       "  '2003-03-28',\n",
       "  '2003-03-31',\n",
       "  '2003-04-01',\n",
       "  '2003-04-02',\n",
       "  '2003-04-03',\n",
       "  '2003-04-04',\n",
       "  '2003-04-07',\n",
       "  '2003-04-08',\n",
       "  '2003-04-09',\n",
       "  '2003-04-10',\n",
       "  '2003-04-11',\n",
       "  '2003-04-14',\n",
       "  '2003-04-15',\n",
       "  '2003-04-16',\n",
       "  '2003-04-17',\n",
       "  '2003-04-21',\n",
       "  '2003-04-22',\n",
       "  '2003-04-23',\n",
       "  '2003-04-24',\n",
       "  '2003-04-25',\n",
       "  '2003-04-28',\n",
       "  '2003-04-29',\n",
       "  '2003-04-30',\n",
       "  '2003-05-01',\n",
       "  '2003-05-02',\n",
       "  '2003-05-05',\n",
       "  '2003-05-06',\n",
       "  '2003-05-07',\n",
       "  '2003-05-08',\n",
       "  '2003-05-09',\n",
       "  '2003-05-12',\n",
       "  '2003-05-13',\n",
       "  '2003-05-14',\n",
       "  '2003-05-15',\n",
       "  '2003-05-16',\n",
       "  '2003-05-19',\n",
       "  '2003-05-20',\n",
       "  '2003-05-21',\n",
       "  '2003-05-22',\n",
       "  '2003-05-23',\n",
       "  '2003-05-27',\n",
       "  '2003-05-28',\n",
       "  '2003-05-29',\n",
       "  '2003-05-30',\n",
       "  '2003-06-02',\n",
       "  '2003-06-03',\n",
       "  '2003-06-04',\n",
       "  '2003-06-05',\n",
       "  '2003-06-06',\n",
       "  '2003-06-09',\n",
       "  '2003-06-10',\n",
       "  '2003-06-11',\n",
       "  '2003-06-12',\n",
       "  '2003-06-13',\n",
       "  '2003-06-16',\n",
       "  '2003-06-17',\n",
       "  '2003-06-18',\n",
       "  '2003-06-19',\n",
       "  '2003-06-20',\n",
       "  '2003-06-23',\n",
       "  '2003-06-24',\n",
       "  '2003-06-25',\n",
       "  '2003-06-26',\n",
       "  '2003-06-27',\n",
       "  '2003-06-30',\n",
       "  '2003-07-01',\n",
       "  '2003-07-02',\n",
       "  '2003-07-03',\n",
       "  '2003-07-07',\n",
       "  '2003-07-08',\n",
       "  '2003-07-09',\n",
       "  '2003-07-10',\n",
       "  '2003-07-11',\n",
       "  '2003-07-14',\n",
       "  '2003-07-15',\n",
       "  '2003-07-16',\n",
       "  '2003-07-17',\n",
       "  '2003-07-18',\n",
       "  '2003-07-21',\n",
       "  '2003-07-22',\n",
       "  '2003-07-23',\n",
       "  '2003-07-24',\n",
       "  '2003-07-25',\n",
       "  '2003-07-28',\n",
       "  '2003-07-29',\n",
       "  '2003-07-30',\n",
       "  '2003-07-31',\n",
       "  '2003-08-01',\n",
       "  '2003-08-04',\n",
       "  '2003-08-05',\n",
       "  '2003-08-06',\n",
       "  '2003-08-07',\n",
       "  '2003-08-08',\n",
       "  '2003-08-11',\n",
       "  '2003-08-12',\n",
       "  '2003-08-13',\n",
       "  '2003-08-14',\n",
       "  '2003-08-15',\n",
       "  '2003-08-18',\n",
       "  '2003-08-19',\n",
       "  '2003-08-20',\n",
       "  '2003-08-21',\n",
       "  '2003-08-22',\n",
       "  '2003-08-25',\n",
       "  '2003-08-26',\n",
       "  '2003-08-27',\n",
       "  '2003-08-28',\n",
       "  '2003-08-29',\n",
       "  '2003-09-02',\n",
       "  '2003-09-03',\n",
       "  '2003-09-04',\n",
       "  '2003-09-05',\n",
       "  '2003-09-08',\n",
       "  '2003-09-09',\n",
       "  '2003-09-10',\n",
       "  '2003-09-11',\n",
       "  '2003-09-12',\n",
       "  '2003-09-15',\n",
       "  '2003-09-16',\n",
       "  '2003-09-17',\n",
       "  '2003-09-18',\n",
       "  '2003-09-19',\n",
       "  '2003-09-22',\n",
       "  '2003-09-23',\n",
       "  '2003-09-24',\n",
       "  '2003-09-25',\n",
       "  '2003-09-26',\n",
       "  '2003-09-29',\n",
       "  '2003-09-30',\n",
       "  '2003-10-01',\n",
       "  '2003-10-02',\n",
       "  '2003-10-03',\n",
       "  '2003-10-06',\n",
       "  '2003-10-07',\n",
       "  '2003-10-08',\n",
       "  '2003-10-09',\n",
       "  '2003-10-10',\n",
       "  '2003-10-13',\n",
       "  '2003-10-14',\n",
       "  '2003-10-15',\n",
       "  '2003-10-16',\n",
       "  '2003-10-17',\n",
       "  '2003-10-20',\n",
       "  '2003-10-21',\n",
       "  '2003-10-22',\n",
       "  '2003-10-23',\n",
       "  '2003-10-24',\n",
       "  '2003-10-27',\n",
       "  '2003-10-28',\n",
       "  '2003-10-29',\n",
       "  '2003-10-30',\n",
       "  '2003-10-31',\n",
       "  '2003-11-03',\n",
       "  '2003-11-04',\n",
       "  '2003-11-05',\n",
       "  '2003-11-06',\n",
       "  '2003-11-07',\n",
       "  '2003-11-10',\n",
       "  '2003-11-11',\n",
       "  '2003-11-12',\n",
       "  '2003-11-13',\n",
       "  '2003-11-14',\n",
       "  '2003-11-17',\n",
       "  '2003-11-18',\n",
       "  '2003-11-19',\n",
       "  '2003-11-20',\n",
       "  '2003-11-21',\n",
       "  '2003-11-24',\n",
       "  '2003-11-25',\n",
       "  '2003-11-26',\n",
       "  '2003-11-28',\n",
       "  '2003-12-01',\n",
       "  '2003-12-02',\n",
       "  '2003-12-03',\n",
       "  '2003-12-04',\n",
       "  '2003-12-05',\n",
       "  '2003-12-08',\n",
       "  '2003-12-09',\n",
       "  '2003-12-10',\n",
       "  '2003-12-11',\n",
       "  '2003-12-12',\n",
       "  '2003-12-15',\n",
       "  '2003-12-16',\n",
       "  '2003-12-17',\n",
       "  '2003-12-18',\n",
       "  '2003-12-19',\n",
       "  '2003-12-22',\n",
       "  '2003-12-23',\n",
       "  '2003-12-24',\n",
       "  '2003-12-26',\n",
       "  '2003-12-29',\n",
       "  '2003-12-30',\n",
       "  '2003-12-31',\n",
       "  '2004-01-02',\n",
       "  '2004-01-05',\n",
       "  '2004-01-06',\n",
       "  '2004-01-07',\n",
       "  '2004-01-08',\n",
       "  '2004-01-09',\n",
       "  '2004-01-12',\n",
       "  '2004-01-13',\n",
       "  '2004-01-14',\n",
       "  '2004-01-15',\n",
       "  '2004-01-16',\n",
       "  '2004-01-20',\n",
       "  '2004-01-21',\n",
       "  '2004-01-22',\n",
       "  '2004-01-23',\n",
       "  '2004-01-26',\n",
       "  '2004-01-27',\n",
       "  '2004-01-28',\n",
       "  '2004-01-29',\n",
       "  '2004-01-30',\n",
       "  '2004-02-02',\n",
       "  '2004-02-03',\n",
       "  '2004-02-04',\n",
       "  '2004-02-05',\n",
       "  '2004-02-06',\n",
       "  '2004-02-09',\n",
       "  '2004-02-10',\n",
       "  '2004-02-11',\n",
       "  '2004-02-12',\n",
       "  '2004-02-13',\n",
       "  '2004-02-17',\n",
       "  '2004-02-18',\n",
       "  '2004-02-19',\n",
       "  '2004-02-20',\n",
       "  '2004-02-23',\n",
       "  '2004-02-24',\n",
       "  ...],\n",
       " 'open': [118.56,\n",
       "  127.0,\n",
       "  124.87,\n",
       "  126.0,\n",
       "  126.44,\n",
       "  122.87,\n",
       "  120.87,\n",
       "  121.69,\n",
       "  122.12,\n",
       "  121.22,\n",
       "  115.62,\n",
       "  117.31,\n",
       "  120.12,\n",
       "  123.5,\n",
       "  122.56,\n",
       "  132.78,\n",
       "  142.0,\n",
       "  142.44,\n",
       "  137.63,\n",
       "  137.25,\n",
       "  139.38,\n",
       "  133.56,\n",
       "  127.44,\n",
       "  135.5,\n",
       "  132.63,\n",
       "  126.47,\n",
       "  130.63,\n",
       "  127.25,\n",
       "  131.69,\n",
       "  123.5,\n",
       "  119.0,\n",
       "  111.5,\n",
       "  109.31,\n",
       "  109.5,\n",
       "  123.5,\n",
       "  126.19,\n",
       "  123.69,\n",
       "  115.0,\n",
       "  122.12,\n",
       "  126.62,\n",
       "  117.19,\n",
       "  127.12,\n",
       "  124.87,\n",
       "  123.25,\n",
       "  118.94,\n",
       "  115.12,\n",
       "  110.81,\n",
       "  112.09,\n",
       "  110.31,\n",
       "  104.06,\n",
       "  101.37,\n",
       "  106.0,\n",
       "  108.06,\n",
       "  104.52,\n",
       "  103.62,\n",
       "  103.0,\n",
       "  99.25,\n",
       "  93.75,\n",
       "  90.5,\n",
       "  86.19,\n",
       "  88.5,\n",
       "  88.0,\n",
       "  87.62,\n",
       "  86.87,\n",
       "  81.75,\n",
       "  93.75,\n",
       "  93.31,\n",
       "  91.97,\n",
       "  93.62,\n",
       "  97.62,\n",
       "  96.75,\n",
       "  96.37,\n",
       "  91.19,\n",
       "  94.69,\n",
       "  91.25,\n",
       "  93.5,\n",
       "  90.56,\n",
       "  98.5,\n",
       "  50.5,\n",
       "  55.75,\n",
       "  53.78,\n",
       "  52.5,\n",
       "  53.78,\n",
       "  53.31,\n",
       "  53.06,\n",
       "  52.81,\n",
       "  52.13,\n",
       "  53.25,\n",
       "  52.5,\n",
       "  52.59,\n",
       "  54.09,\n",
       "  57.0,\n",
       "  58.13,\n",
       "  58.5,\n",
       "  57.13,\n",
       "  58.25,\n",
       "  58.5,\n",
       "  55.19,\n",
       "  55.0,\n",
       "  54.36,\n",
       "  52.56,\n",
       "  50.31,\n",
       "  49.84,\n",
       "  50.0,\n",
       "  52.28,\n",
       "  49.16,\n",
       "  50.31,\n",
       "  49.0,\n",
       "  45.56,\n",
       "  49.47,\n",
       "  47.88,\n",
       "  47.94,\n",
       "  48.13,\n",
       "  48.0,\n",
       "  46.84,\n",
       "  47.59,\n",
       "  47.25,\n",
       "  46.88,\n",
       "  48.38,\n",
       "  51.38,\n",
       "  50.25,\n",
       "  50.63,\n",
       "  51.47,\n",
       "  54.67,\n",
       "  56.5,\n",
       "  57.25,\n",
       "  57.88,\n",
       "  59.0,\n",
       "  58.97,\n",
       "  61.31,\n",
       "  62.66,\n",
       "  61.38,\n",
       "  59.13,\n",
       "  61.63,\n",
       "  58.69,\n",
       "  57.34,\n",
       "  56.75,\n",
       "  58.56,\n",
       "  57.75,\n",
       "  55.25,\n",
       "  59.75,\n",
       "  59.41,\n",
       "  58.5,\n",
       "  50.31,\n",
       "  52.75,\n",
       "  53.31,\n",
       "  51.75,\n",
       "  49.31,\n",
       "  28.19,\n",
       "  26.69,\n",
       "  24.94,\n",
       "  22.37,\n",
       "  23.5,\n",
       "  22.69,\n",
       "  22.62,\n",
       "  21.62,\n",
       "  20.12,\n",
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       "  20.25,\n",
       "  22.31,\n",
       "  21.69,\n",
       "  19.44,\n",
       "  19.16,\n",
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       "  20.27,\n",
       "  20.69,\n",
       "  19.06,\n",
       "  18.81,\n",
       "  18.87,\n",
       "  19.12,\n",
       "  19.75,\n",
       "  19.44,\n",
       "  21.12,\n",
       "  23.0,\n",
       "  22.44,\n",
       "  21.5,\n",
       "  21.37,\n",
       "  19.87,\n",
       "  19.36,\n",
       "  18.75,\n",
       "  19.94,\n",
       "  20.03,\n",
       "  19.5,\n",
       "  19.19,\n",
       "  18.59,\n",
       "  19.19,\n",
       "  18.81,\n",
       "  18.86,\n",
       "  19.87,\n",
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       "  18.09,\n",
       "  16.69,\n",
       "  17.0,\n",
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       "  14.63,\n",
       "  14.44,\n",
       "  14.81,\n",
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       "  15.25,\n",
       "  15.56,\n",
       "  15.03,\n",
       "  14.56,\n",
       "  14.56,\n",
       "  14.38,\n",
       "  13.78,\n",
       "  14.25,\n",
       "  14.13,\n",
       "  14.88,\n",
       "  14.34,\n",
       "  14.38,\n",
       "  14.69,\n",
       "  14.88,\n",
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       "  18.14,\n",
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       "  16.94,\n",
       "  16.81,\n",
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       "  17.56,\n",
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       "  20.62,\n",
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       "  19.5,\n",
       "  19.56,\n",
       "  21.56,\n",
       "  21.5,\n",
       "  20.69,\n",
       "  21.12,\n",
       "  20.5,\n",
       "  20.16,\n",
       "  20.66,\n",
       "  20.56,\n",
       "  20.5,\n",
       "  19.06,\n",
       "  19.94,\n",
       "  19.19,\n",
       "  19.69,\n",
       "  19.0,\n",
       "  19.19,\n",
       "  18.25,\n",
       "  19.06,\n",
       "  18.62,\n",
       "  19.06,\n",
       "  19.28,\n",
       "  19.37,\n",
       "  17.81,\n",
       "  18.31,\n",
       "  19.37,\n",
       "  20.72,\n",
       "  21.31,\n",
       "  20.69,\n",
       "  20.62,\n",
       "  19.69,\n",
       "  18.87,\n",
       "  18.5,\n",
       "  20.87,\n",
       "  19.0,\n",
       "  19.75,\n",
       "  20.72,\n",
       "  19.78,\n",
       "  20.37,\n",
       "  22.06,\n",
       "  23.13,\n",
       "  21.94,\n",
       "  22.08,\n",
       "  21.77,\n",
       "  22.55,\n",
       "  22.09,\n",
       "  21.36,\n",
       "  19.76,\n",
       "  20.6,\n",
       "  20.8,\n",
       "  20.69,\n",
       "  20.9,\n",
       "  22.98,\n",
       "  21.42,\n",
       "  22.09,\n",
       "  21.2,\n",
       "  21.57,\n",
       "  25.55,\n",
       "  24.93,\n",
       "  24.34,\n",
       "  24.33,\n",
       "  24.21,\n",
       "  25.17,\n",
       "  25.2,\n",
       "  26.7,\n",
       "  25.41,\n",
       "  26.34,\n",
       "  25.97,\n",
       "  24.24,\n",
       "  25.62,\n",
       "  25.35,\n",
       "  24.14,\n",
       "  24.21,\n",
       "  23.01,\n",
       "  22.89,\n",
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       "  22.21,\n",
       "  21.89,\n",
       "  22.0,\n",
       "  ...],\n",
       " 'close': [130.31,\n",
       "  122.0,\n",
       "  128.0,\n",
       "  125.69,\n",
       "  122.87,\n",
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       "  20.56,\n",
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       "  20.12,\n",
       "  21.62,\n",
       "  23.0,\n",
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       "  20.42,\n",
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       "  20.45,\n",
       "  20.38,\n",
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       "  20.89,\n",
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       "  19.7,\n",
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       "  19.81,\n",
       "  20.41,\n",
       "  20.78,\n",
       "  21.15,\n",
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       "  21.37,\n",
       "  21.28,\n",
       "  22.17,\n",
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       "  23.36,\n",
       "  23.0,\n",
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       "  24.12,\n",
       "  24.2,\n",
       "  22.85,\n",
       "  22.72,\n",
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       "  22.61,\n",
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       "  23.01,\n",
       "  23.07,\n",
       "  22.52,\n",
       "  22.68,\n",
       "  22.56,\n",
       "  22.32,\n",
       "  22.26,\n",
       "  21.79,\n",
       "  22.42,\n",
       "  22.71,\n",
       "  22.67,\n",
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       "  23.8,\n",
       "  23.73,\n",
       "  23.0,\n",
       "  23.16,\n",
       "  23.26,\n",
       "  22.47,\n",
       "  22.4,\n",
       "  22.19,\n",
       "  22.36,\n",
       "  ...],\n",
       " 'volume': [38478000,\n",
       "  11136800,\n",
       "  11565200,\n",
       "  7520000,\n",
       "  9767600,\n",
       "  9690800,\n",
       "  9884400,\n",
       "  8900800,\n",
       "  10864400,\n",
       "  15321200,\n",
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       "  ...]}"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AAPL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "{'date': ['2004-08-19',\n",
       "  '2004-08-20',\n",
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       "  '2008-03-13',\n",
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       "  '2008-03-26',\n",
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       "  '2008-05-07',\n",
       "  '2008-05-08',\n",
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       "  '2008-05-14',\n",
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       "  '2008-06-02',\n",
       "  '2008-06-03',\n",
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       "  '2008-06-05',\n",
       "  '2008-06-06',\n",
       "  '2008-06-09',\n",
       "  '2008-06-10',\n",
       "  '2008-06-11',\n",
       "  '2008-06-12',\n",
       "  '2008-06-13',\n",
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       "  '2008-06-17',\n",
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       "  '2008-06-23',\n",
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       "  '2008-07-02',\n",
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       "  '2008-07-08',\n",
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       "  '2008-07-15',\n",
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       "  '2008-07-25',\n",
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       "  '2008-07-30',\n",
       "  '2008-07-31',\n",
       "  '2008-08-01',\n",
       "  '2008-08-04',\n",
       "  '2008-08-05',\n",
       "  '2008-08-06',\n",
       "  '2008-08-07',\n",
       "  ...],\n",
       " 'open': [100.0,\n",
       "  101.01,\n",
       "  110.75,\n",
       "  111.24,\n",
       "  104.96,\n",
       "  104.95,\n",
       "  108.1,\n",
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       "  102.3,\n",
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       "  297.5,\n",
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       "  291.3,\n",
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       "  285.51,\n",
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       "  285.89,\n",
       "  294.83,\n",
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       "  309.0,\n",
       "  308.73,\n",
       "  299.52,\n",
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       "  308.41,\n",
       "  311.5,\n",
       "  313.0,\n",
       "  319.5,\n",
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       "  314.22,\n",
       "  306.68,\n",
       "  314.22,\n",
       "  313.63,\n",
       "  319.95,\n",
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       "  305.2,\n",
       "  302.0,\n",
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       "  356.6,\n",
       "  355.27,\n",
       "  360.24,\n",
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       "  395.1,\n",
       "  394.25,\n",
       "  386.67,\n",
       "  378.36,\n",
       "  395.12,\n",
       "  392.12,\n",
       "  394.38,\n",
       "  396.2,\n",
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       "  403.49,\n",
       "  399.17,\n",
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       "  409.2,\n",
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       "  405.3,\n",
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       "  412.5,\n",
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       "  419.11,\n",
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       "  432.2,\n",
       "  427.86,\n",
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       "  427.98,\n",
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       "  422.52,\n",
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       "  464.31,\n",
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       "  451.17,\n",
       "  438.7,\n",
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       "  435.0,\n",
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       "  403.82,\n",
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       "  385.31,\n",
       "  382.99,\n",
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       "  371.2,\n",
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       "  341.27,\n",
       "  345.67,\n",
       "  369.86,\n",
       "  366.44,\n",
       "  367.15,\n",
       "  365.61,\n",
       "  377.3,\n",
       "  381.27,\n",
       "  393.2,\n",
       "  368.56,\n",
       "  364.28,\n",
       "  384.3,\n",
       "  380.91,\n",
       "  365.02,\n",
       "  353.93,\n",
       "  355.39,\n",
       "  343.5,\n",
       "  340.93,\n",
       "  337.14,\n",
       "  350.77,\n",
       "  348.61,\n",
       "  338.8,\n",
       "  342.34,\n",
       "  350.01,\n",
       "  339.75,\n",
       "  342.35,\n",
       "  368.62,\n",
       "  367.09,\n",
       "  371.71,\n",
       "  379.94,\n",
       "  389.19,\n",
       "  388.74,\n",
       "  389.53,\n",
       "  389.9,\n",
       "  408.2,\n",
       "  406.49,\n",
       "  412.41,\n",
       "  407.08,\n",
       "  416.42,\n",
       "  409.0,\n",
       "  408.63,\n",
       "  403.45,\n",
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       "  ...],\n",
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       "  342.38,\n",
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       "  486.34,\n",
       "  479.12,\n",
       "  ...],\n",
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       "  ...]}"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GOOG"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 表格的数据是数组形式的，取值按照数组的方式取"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'dict' object has no attribute 'date'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-46-1a9ed73bfad6>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# 数组的表格不可以用字典的方式取\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mAAPL\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdate\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m: 'dict' object has no attribute 'date'"
     ]
    }
   ],
   "source": [
    "# 数组的表格不可以用字典的方式取，\n",
    "\n",
    "AAPL.date.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['2000-03-01', '2000-03-02', '2000-03-03', ..., '2013-02-27',\n",
       "       '2013-02-28', '2013-03-01'], dtype='<U10')"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "aapl=np.array(AAPL[\"date\"])\n",
    "aapl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 数据转换为时间类型\n",
    "\n",
    "# 方法1：封装函数，因为有两个表格的数据，不用每一次都转换\n",
    "def datetime(x):\n",
    "    return np.array(x, dtype=np.datetime64)\n",
    "\n",
    "\n",
    "# 方法2：每一个表格都要弄一次，比较麻烦\n",
    "# aapl_date=np.array(AAPL[\"date\"],dtype=np.datetime64)\n",
    "# aapl_date\n",
    "\n",
    "# goog_date=np.array(GOOG[\"date\"],dtype=np.datetime64)\n",
    "# goog_date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 数据准备\n",
    "\n",
    "\n",
    "aapl_source = ColumnDataSource(data=dict(\n",
    "    aapl_date=datetime(AAPL['date']),\n",
    "    aapl_close=AAPL['adj_close'],\n",
    "))\n",
    "\n",
    "goog_source = ColumnDataSource(data=dict(\n",
    "    goog_date=datetime(GOOG['date']),\n",
    "    goog_close=GOOG['adj_close'],\n",
    "))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[2148]}},\"selected\":{\"id\":\"4084\"},\"selection_policy\":{\"id\":\"4085\"}},\"id\":\"4011\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"mantissas\":[1,2,5],\"max_interval\":500.0,\"num_minor_ticks\":0},\"id\":\"4588\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{},\"id\":\"4056\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#2f7bce\",\"line_width\":3,\"x\":{\"field\":\"goog_date\"},\"y\":{\"field\":\"goog_close\"}},\"id\":\"4604\",\"type\":\"Line\"},{\"attributes\":{\"axis\":{\"id\":\"4557\"},\"dimension\":1,\"grid_line_alpha\":0.1,\"grid_line_color\":\"black\",\"ticker\":null},\"id\":\"4560\",\"type\":\"Grid\"},{\"attributes\":{\"base\":60,\"mantissas\":[1,2,5,10,15,20,30],\"max_interval\":1800000.0,\"min_interval\":1000.0,\"num_minor_ticks\":0},\"id\":\"4589\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"days\":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]},\"id\":\"4591\",\"type\":\"DaysTicker\"},{\"attributes\":{\"line_alpha\":0.6,\"line_color\":\"#cf435d\",\"line_width\":3,\"x\":{\"field\":\"aapl_date\"},\"y\":{\"field\":\"aapl_close\"}},\"id\":\"4576\",\"type\":\"Line\"}],\"root_ids\":[\"4542\"]},\"title\":\"Bokeh Application\",\"version\":\"2.1.1\"}};\n",
       "  var render_items = [{\"docid\":\"92ed3fec-7782-40bb-abf1-dfb5ab352c32\",\"root_ids\":[\"4542\"],\"roots\":{\"4542\":\"f4d78086-ac9a-4a43-bc74-bf1f4cc0136a\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "4542"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 画布\n",
    "p = figure(x_axis_type=\"datetime\", title=\"Normalized Stock Closing Prices\",\n",
    "              plot_width=800, plot_height=350)\n",
    "\n",
    "# 其他\n",
    "p.background_fill_color = \"#f0f0f0\" #图表的背景色\n",
    "p.xgrid.grid_line_color = None      #绘制x网格线的颜色\n",
    "p.ygrid.grid_line_color = \"black\"\n",
    "p.ygrid.grid_line_alpha = 0.1\n",
    "p.xaxis.axis_label = 'Date'         #图例\n",
    "p.yaxis.axis_label = 'Normalized Price'\n",
    "\n",
    "\n",
    "p.line('aapl_date','aapl_close',color=\"#cf435d\",alpha=0.6,line_width=3,source=aapl_source,legend_label=\"apple\")\n",
    "p.line('goog_date','goog_close', color='#2f7bce', alpha=0.6,line_width=3,source=goog_source,legend_label=\"google\")\n",
    "p.legend.location=\"top_left\"\n",
    "p.legend.click_policy=\"hide\" # 点击图例显示隐藏数据\n",
    "\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
